At present, many companies have begun to use artificial intelligence and machine learning, and the application of these technologies will only have a greater impact on the job. Although this is a good thing for companies that want to improve their performance, many employees worry that robots will replace their jobs in the next few years. If we want to not be replaced, we have to make some changes in our way of thinking in order to improve our competitiveness in the workplace in the future.
Members of the Forbes Coaches Council shared some skills that you can acquire in your future career.
1. Learn to understand the value of data
Although new innovations will require everyone to become more and more familiar with technology, this does not mean that everyone can be proficient in technology. Technology is a powerful force in learning to compute and interpret data. This skill will witness an increase in demand for labour and will help consolidate the value of being an employee or potential leader.
2. Be honest about your skills gap
As a responsible professional, one of the responsibilities is to maintain the status quo in the changing technology and customer needs. Be honest about areas where you need to speed up, rather than trying to hide them, trying to reach the level you want to achieve in order to maintain a relationship with the future. Instead of blaming change, embrace it.
3. Focus on building relationships
Re-focusing on AI and machine learning as tools can replace some steps to provide higher value and services. But they will not replace the core of business: interpersonal relationships. Therefore, we should keep insight and embrace differences in interests and values. First, it gives you more time to focus on customer-centric priorities. Secondly, for leaders, it can help you build and maintain interpersonal relationships and strengthen your professional skills.
5. Continuous learning
Artificial intelligence and machine learning are changing the valuable skills of the past, but they also create new opportunities for career development. Daily work will be automated and people will have greater opportunities to make strategic and far-sighted decisions with their organizations. Invest in learning a new skill, whether it's about using new technology, building it, or expanding it through leadership.
6. Embrace opportunities for change
Destructive new technologies lead to outdated processes, methods and practices. Instead of fighting it, embrace it! Now that you understand the old approach, you can better transform infrastructure and integrate it with new technologies. This will require you to learn as much as possible about the order of the emerging world and look for opportunities to become the masters of change.
7. Improve your communication skills
I see AI as a tool - a resource that can improve productivity and efficiency. With that in mind, your career impact goes beyond what you do every day. Your communication skills, problem solving through logic, and empathy with customers and colleagues are important. In the context of our changing economy, strong communication and leadership skills are essential.
8. Find ways to improve efficiency
To give yourself the opportunity to take on more tasks and projects and become a good employee, say yes to these opportunities because you will become more skilled, valuable and versatile. You might think, "I'm too busy!" That's right, but learn to find ways to use AI and machine learning in your role to improve efficiency (reduce costs). This is valuable - and can prove that you are valuable to the company.
9. Develop your "insight"
Artificial intelligence is good at discovering trends and processing large data as well as large amounts of data. To some extent, it can also predict. But if you ask it, "Why is that so?" Everything began to fall apart. Artificial intelligence and machine learning are good at processing data, but not good at information. Information is a subset of data. Access to real-life information, opinions and inferences is the way we (humans) increase the real value of data. To defeat machines, we need insight.
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